EP4145353A4 - Verfahren und vorrichtung zur konstruktion eines neuronalen netzwerks - Google Patents
Verfahren und vorrichtung zur konstruktion eines neuronalen netzwerks Download PDFInfo
- Publication number
- EP4145353A4 EP4145353A4 EP21813687.7A EP21813687A EP4145353A4 EP 4145353 A4 EP4145353 A4 EP 4145353A4 EP 21813687 A EP21813687 A EP 21813687A EP 4145353 A4 EP4145353 A4 EP 4145353A4
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- EP
- European Patent Office
- Prior art keywords
- constructing
- neuronal network
- neuronal
- network
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/096—Transfer learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/96—Management of image or video recognition tasks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/806—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Data Mining & Analysis (AREA)
- Software Systems (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Mathematical Physics (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Databases & Information Systems (AREA)
- Medical Informatics (AREA)
- Biodiversity & Conservation Biology (AREA)
- Neurology (AREA)
- Image Analysis (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010448652.7A CN111797983B (zh) | 2020-05-25 | 2020-05-25 | 一种神经网络构建方法以及装置 |
| PCT/CN2021/082222 WO2021238366A1 (zh) | 2020-05-25 | 2021-03-23 | 一种神经网络构建方法以及装置 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| EP4145353A1 EP4145353A1 (de) | 2023-03-08 |
| EP4145353A4 true EP4145353A4 (de) | 2023-10-25 |
Family
ID=72806177
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP21813687.7A Pending EP4145353A4 (de) | 2020-05-25 | 2021-03-23 | Verfahren und vorrichtung zur konstruktion eines neuronalen netzwerks |
Country Status (4)
| Country | Link |
|---|---|
| US (1) | US20230089380A1 (de) |
| EP (1) | EP4145353A4 (de) |
| CN (1) | CN111797983B (de) |
| WO (1) | WO2021238366A1 (de) |
Families Citing this family (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10635813B2 (en) | 2017-10-06 | 2020-04-28 | Sophos Limited | Methods and apparatus for using machine learning on multiple file fragments to identify malware |
| US11003774B2 (en) | 2018-01-26 | 2021-05-11 | Sophos Limited | Methods and apparatus for detection of malicious documents using machine learning |
| US11941491B2 (en) | 2018-01-31 | 2024-03-26 | Sophos Limited | Methods and apparatus for identifying an impact of a portion of a file on machine learning classification of malicious content |
| WO2020030913A1 (en) | 2018-08-07 | 2020-02-13 | Sophos Limited | Methods and apparatus for management of a machine-learning model to adapt to changes in landscape of potentially malicious artifacts |
| US11947668B2 (en) | 2018-10-12 | 2024-04-02 | Sophos Limited | Methods and apparatus for preserving information between layers within a neural network |
| CN111797983B (zh) * | 2020-05-25 | 2024-12-03 | 华为技术有限公司 | 一种神经网络构建方法以及装置 |
| CN112633471B (zh) * | 2020-12-17 | 2023-09-26 | 苏州浪潮智能科技有限公司 | 构建神经网络架构搜索框架的方法、系统、设备及介质 |
| CN112686371A (zh) * | 2020-12-25 | 2021-04-20 | 深圳前海微众银行股份有限公司 | 网络结构搜索方法、装置、设备、存储介质及程序产品 |
| CN114692861B (zh) * | 2020-12-28 | 2026-01-16 | 华为技术有限公司 | 计算图更新方法、计算图处理方法以及相关设备 |
| CN113031437B (zh) * | 2021-02-26 | 2022-10-25 | 同济大学 | 一种基于动态模型强化学习的倒水服务机器人控制方法 |
| US12010129B2 (en) * | 2021-04-23 | 2024-06-11 | Sophos Limited | Methods and apparatus for using machine learning to classify malicious infrastructure |
| CN112990448B (zh) * | 2021-04-26 | 2021-08-03 | 清华大学 | 用于计算的方法、计算系统、计算设备和介质 |
| CN115345305A (zh) * | 2021-05-12 | 2022-11-15 | 华为云计算技术有限公司 | 一种推理系统、方法、装置及相关设备 |
| CN113920514B (zh) * | 2021-06-18 | 2024-11-12 | 上海悠络客电子科技股份有限公司 | 一种面向目标检测的高效进化神经网络架构搜索方法 |
| CN113743606B (zh) * | 2021-09-08 | 2024-12-17 | 广州文远知行科技有限公司 | 一种神经网络的搜索方法、装置、计算机设备和存储介质 |
| CN113792876B (zh) | 2021-09-16 | 2023-08-29 | 北京百度网讯科技有限公司 | 骨干网络的生成方法、装置、设备以及存储介质 |
| CN113988272B (zh) * | 2021-11-08 | 2025-11-18 | 上海商汤智能科技有限公司 | 一种生成神经网络的方法、装置、计算机设备和存储介质 |
| CN114492765B (zh) * | 2022-02-24 | 2024-09-13 | 腾讯科技(深圳)有限公司 | 一种模型优化方法、装置、设备及存储介质、程序产品 |
| CN114995782B (zh) * | 2022-08-03 | 2022-10-25 | 上海登临科技有限公司 | 数据处理方法、装置、设备和可读存储介质 |
| CN116205905B (zh) * | 2023-04-25 | 2023-07-21 | 合肥中科融道智能科技有限公司 | 基于移动端的配电网施工安全及质量图像检测方法及系统 |
| CN117234095B (zh) * | 2023-08-18 | 2024-04-02 | 浙江雨林电子科技有限公司 | 一种全屋家居无线智能控制方法及系统 |
| CN117010447B (zh) * | 2023-10-07 | 2024-01-23 | 成都理工大学 | 基于端到端的可微架构搜索方法 |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200143231A1 (en) * | 2018-11-02 | 2020-05-07 | Microsoft Technology Licensing, Llc | Probabilistic neural network architecture generation |
Family Cites Families (16)
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| CN1889560A (zh) * | 2005-08-03 | 2007-01-03 | 华为技术有限公司 | 网际协议多媒体子系统中面向用户的网络拓扑隐藏方法 |
| US10346727B2 (en) * | 2016-10-28 | 2019-07-09 | Adobe Inc. | Utilizing a digital canvas to conduct a spatial-semantic search for digital visual media |
| CN108229647A (zh) * | 2017-08-18 | 2018-06-29 | 北京市商汤科技开发有限公司 | 神经网络结构的生成方法和装置、电子设备、存储介质 |
| WO2019108923A1 (en) * | 2017-11-30 | 2019-06-06 | Google Llc | Neural architecture search using a performance prediction neural network |
| US11164079B2 (en) * | 2017-12-15 | 2021-11-02 | International Business Machines Corporation | Multi-GPU deep learning using CPUs |
| CN108917583B (zh) * | 2018-05-18 | 2019-04-23 | 长安大学 | 一种顾及对流层延迟影响的超高层建筑形变监测新方法 |
| CN109284820A (zh) * | 2018-10-26 | 2019-01-29 | 北京图森未来科技有限公司 | 一种深度神经网络的结构搜索方法及装置 |
| CN120509449A (zh) * | 2019-01-23 | 2025-08-19 | 谷歌有限责任公司 | 用于神经网络的复合模型缩放 |
| CN110175671B (zh) * | 2019-04-28 | 2022-12-27 | 华为技术有限公司 | 神经网络的构建方法、图像处理方法及装置 |
| CN110097176A (zh) * | 2019-05-07 | 2019-08-06 | 东华理工大学 | 一种应用于空气质量大数据异常检测的神经网络结构搜索方法 |
| CN110334802B (zh) * | 2019-05-23 | 2025-02-18 | 腾讯科技(深圳)有限公司 | 一种神经网络模型的构建方法、装置、设备及存储介质 |
| CN110363810B (zh) * | 2019-06-14 | 2021-07-16 | 北京百度网讯科技有限公司 | 建立图像检测模型的方法、装置、设备和计算机存储介质 |
| CN111126564B (zh) * | 2019-11-27 | 2023-08-08 | 东软集团股份有限公司 | 一种神经网络结构搜索方法、装置及设备 |
| US11475313B2 (en) * | 2020-02-13 | 2022-10-18 | International Business Machines Corporation | Unsupervised, semi-supervised, and supervised learning using deep learning based probabilistic generative models |
| US11665180B2 (en) * | 2020-02-28 | 2023-05-30 | International Business Machines Corporation | Artificially intelligent security incident and event management |
| CN111797983B (zh) * | 2020-05-25 | 2024-12-03 | 华为技术有限公司 | 一种神经网络构建方法以及装置 |
-
2020
- 2020-05-25 CN CN202010448652.7A patent/CN111797983B/zh active Active
-
2021
- 2021-03-23 EP EP21813687.7A patent/EP4145353A4/de active Pending
- 2021-03-23 WO PCT/CN2021/082222 patent/WO2021238366A1/zh not_active Ceased
-
2022
- 2022-11-23 US US17/993,430 patent/US20230089380A1/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200143231A1 (en) * | 2018-11-02 | 2020-05-07 | Microsoft Technology Licensing, Llc | Probabilistic neural network architecture generation |
Non-Patent Citations (2)
| Title |
|---|
| See also references of WO2021238366A1 * |
| WEI WEN ET AL: "AutoGrow: Automatic Layer Growing in Deep Convolutional Networks", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 7 June 2019 (2019-06-07), XP081374300 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111797983B (zh) | 2024-12-03 |
| EP4145353A1 (de) | 2023-03-08 |
| US20230089380A1 (en) | 2023-03-23 |
| CN111797983A (zh) | 2020-10-20 |
| WO2021238366A1 (zh) | 2021-12-02 |
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